Biostatistics, Doctor of Philosophy (Ph.D.)
Summary of PhD in Biostatistics Program Course Requirements
- Prerequisites/Admission requirement (preferred): Calculus (preferably 3 semesters including multivariable calculus), Linear algebra.
- Course waiving policy for students who have taken similar (graduate-level) courses from other institutions.
- All students are strongly encouraged to attend the biweekly seminar every semester.
- Students entering with a relevant master's degree in biostatistics or statistics are likely to have completed several of the courses required for the Ph.D. program. For this reason, we outline two programs of study: I. Students with a relevant master's degree; II. Students without a relevant master's degree.
- Students advance to candidacy after successfully completing the comprehensive exam and dissertation proposal.
I) Students entering with a relevant master's degree (e.g. MS/MPH in Biostatistics):
The total credits for PhD in Biostatistics will be 48 (36 course credits + 12 dissertation credits) if students have a prior MS/MPH degree in biostatistics.
| Course | Title | Credits |
|---|---|---|
| IA. Core Courses 1 | ||
| EPIB652 | Categorical Data Analysis | 3 |
| EPIB653 | Applied Survival Data Analysis | 3 |
| EPIB655 | Longitudinal Data Analysis | 3 |
| EPIB680 | (Linear Model) | 3 |
| EPIB610 | Foundations of Epidemiology | 3 |
| SPHL600 | Foundations of Public Health | 3 |
| STAT700 | Mathematical Statistics I | 3 |
| STAT701 | Mathematical Statistics II | 3 |
| IB. Elective Courses 2 | 12 | |
| Intermediate Epidemiology | ||
| Epidemiologic Study Design | ||
| Health Survey Design and Analysis | ||
| Applied Multilevel Modeling in Health Research | ||
| Clinical Trials: Design and Analysis | ||
| Applied Bayesian Data Analysis | ||
| Spatial Statistics for Public Health Data | ||
| Analysis of National Health Survey Data | ||
| Applied Multivariate Data Analysis | ||
| Missing Data Analysis | ||
EPIB667 | (Applied Machine Learning with Python) | |
EPIB681 | (Causal Inference) | |
EPIB682 | (Statistical Learning for Health Data Analysis) | |
EPIB683 | (High-throughput Data Analysis) | |
| Epidemiologic Research Using Electronic Health Records Data (Electronic Health Record Data Analysis) | ||
| Introduction to R for Health Data Analysis | ||
| IC. Dissertation Credits 3 | 12 | |
| Doctoral Dissertation Research | ||
| Total Credits | 48 | |
- 1
The 8 core courses are required for students with a MS/MPH degree in Biostatistics (24 credits). It is anticipated that students with a relevant master’s degree in biostatistics from accredited school of public health would have taken core courses such as EPIB650 (Biostatistics I), EPIB651 (Applied Regression Analysis) and EPIB697 (Public Health Data Management).
- 2
With advisement, students will be able to choose elective courses (12 credits) both within and outside of EPIB (MATH, JPSM, CMSC, UMSOM).
- 3
Students are required to complete 12 dissertation credits after passing the Comprehensive Exam.
II) Students entering WITHOUT a relevant master's degree (e.g. MS/MPH in Biostatistics):
The total credits will be 60 for students without prior MS/MPH degree in biostatistics (48 course credits + 12 dissertation credits).
The table below provides the list of 11 core courses for students without a relevant master degree (33 credits).
| Course | Title | Credits |
|---|---|---|
| IIA. Core Courses | ||
| EPIB650 | Biostatistics I | 3 |
| EPIB651 | Applied Regression Analysis | 3 |
| EPIB652 | Categorical Data Analysis | 3 |
| EPIB653 | Applied Survival Data Analysis | 3 |
| EPIB655 | Longitudinal Data Analysis | 3 |
| EPIB680 | (Linear Model) | 3 |
| EPIB697 | Public Health Data Management | 3 |
| EPIB610 | Foundations of Epidemiology | 3 |
| SPHL600 | Foundations of Public Health | 3 |
| STAT700 | Mathematical Statistics I | 3 |
| STAT701 | Mathematical Statistics II | 3 |
| IIB. Elective Courses | 15 | |
| Intermediate Epidemiology | ||
| Epidemiologic Study Design | ||
| Health Survey Design and Analysis | ||
| Applied Multilevel Modeling in Health Research | ||
| Clinical Trials: Design and Analysis | ||
| Applied Bayesian Data Analysis | ||
| Spatial Statistics for Public Health Data | ||
| Analysis of National Health Survey Data | ||
| Applied Multivariate Data Analysis | ||
| Missing Data Analysis | ||
EPIB667 | (Applied Machine Learning with Python) | |
EPIB681 | (Causal Inference) | |
EPIB682 | (Statistical Learning for Health Data Analysis) | |
EPIB683 | (High-throughput Data Analysis) | |
| Epidemiologic Research Using Electronic Health Records Data (Electronic Health Record Data Analysis) | ||
| Introduction to R for Health Data Analysis | ||
| IIC. Dissertation Credits 2 | 12 | |
| Doctoral Dissertation Research 2 | ||
| Total Credits | 60 | |
- 1
With advisement, students will be able to choose elective courses (15 credits) both within and outside of EPIB (MATH, JPSM, CMSC, UMSOM).
- 2
Students are also required to complete 12 dissertation credits after passing the Comprehensive Exam.